AltexSoft

FEBRUARY 11, 2023

Proficiency in programming languages Even though in most cases data architects don’t have to code themselves, proficiency in several popular programming languages is a must. They also must understand the main principles of how these services are implemented in data collection, storage and data visualization.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Knowledge Hut

NOVEMBER 28, 2023

As a Data Engineer, you must: Work with the uninterrupted flow of data between your server and your application. Work closely with software engineers and data scientists. Java can be used to build APIs and move them to destinations in the appropriate logistics of data landscapes.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Knowledge Hut

JUNE 20, 2023

Languages Python, SQL, Java, Scala R, C++, Java Script, and Python Tools Kafka, Tableau, Snowflake, etc. Skills A data engineer should have good programming and analytical skills with big data knowledge. Additionally, they create and test the systems necessary to gather and process data for predictive modelling.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Knowledge Hut

FEBRUARY 27, 2023

Data engineers can communicate data trends and make sense of the data, which large and small organizations demand to perform major data engineer jobs in Singapore. Who is Data Engineer, and What Do They Do? A data engineer can be a generalist, pipeline-centric, or database-centric.

Data Engineering 52

Data Engineering Data Engineer Database-centric Pipeline-centric 52

ProjectPro

DECEMBER 16, 2021

In that case, Data Science is a comparatively broader and generalist role than Machine Learning Engineer, which is quite a specialist role and, therefore, sees a lot more vacancies, according to Indeed. They should be highly proficient with Python, R, and Java/JS programming.

Machine Learning 52

Machine Learning Engineering Pipeline-centric Database-centric 52

Knowledge Hut

DECEMBER 26, 2023

However, as we progressed, data became complicated, more unstructured, or, in most cases, semi-structured. This mainly happened because data that is collected in recent times is vast and the source of collection of such data is varied, for example, data collected from text files, financial documents, multimedia data, sensors, etc.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98